# tf.compat.v1.random_uniform_initializer

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|---|
| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/init_ops.py#L397-L484) |

Initializer that generates tensors with a uniform distribution.

#### View aliases


**Compat aliases for migration**

See
[Migration guide](https://www.tensorflow.org/guide/migrate) for
more details.

[`tf.compat.v1.initializers.random_uniform`](https://www.tensorflow.org/api_docs/python/tf/compat/v1/random_uniform_initializer)

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    tf.compat.v1.random_uniform_initializer(
        minval=0.0,
        maxval=None,
        seed=None,
        dtype=https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/dtypes#float32
    )

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## Migrate to TF2

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> [!CAUTION]
> **Caution:** This API was designed for TensorFlow v1. Continue reading for details on how to migrate from this API to a native TensorFlow v2 equivalent. See the [TensorFlow v1 to TensorFlow v2 migration guide](https://www.tensorflow.org/guide/migrate) for instructions on how to migrate the rest of your code.

Although it is a legacy compat.v1 API, this symbol is compatible with eager
execution and [`tf.function`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/function).

To switch to TF2, switch to using either
[`tf.initializers.RandomUniform`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/keras/initializers/RandomUniform) or [`tf.keras.initializers.RandomUniform`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/keras/initializers/RandomUniform)
(neither from [`compat.v1`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/compat/v1)) and
pass the dtype when calling the initializer. Keep in mind that
the default minval, maxval and the behavior of fixed seeds have changed.

#### Structural Mapping to TF2

Before:

    initializer = tf.compat.v1.random_uniform_initializer(
      minval=minval,
      maxval=maxval,
      seed=seed,
      dtype=dtype)

    weight_one = tf.Variable(initializer(shape_one))
    weight_two = tf.Variable(initializer(shape_two))

After:

    initializer = tf.initializers.RandomUniform(
      minval=minval,
      maxval=maxval,
      seed=seed)

    weight_one = tf.Variable(initializer(shape_one, dtype=dtype))
    weight_two = tf.Variable(initializer(shape_two, dtype=dtype))

#### How to Map Arguments

| TF1 Arg Name | TF2 Arg Name | Note |
|---|---|---|
| `minval` | `minval` | Default changes from 0 to -0.05 |
| `maxval` | `maxval` | Default changes from 1.0 to 0.05 |
| `seed` | `seed` |   |
| `dtype` | `dtype` | The TF2 native api only takes it as a `__call__` arg, not a constructor arg. |
| `partition_info` | - | (`__call__` arg in TF1) Not supported |

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## Description

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| ## Args ||
|---|---|
| `minval` | A python scalar or a scalar tensor. Lower bound of the range of random values to generate. |
| `maxval` | A python scalar or a scalar tensor. Upper bound of the range of random values to generate. Defaults to 1 for float types. |
| `seed` | A Python integer. Used to create random seeds. See [`tf.compat.v1.set_random_seed`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/compat/v1/set_random_seed) for behavior. |
| `dtype` | Default data type, used if no `dtype` argument is provided when calling the initializer. |

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## Methods

### `from_config`

[View source](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/init_ops.py#L75-L94)

    @classmethod
    from_config(
        config
    )

Instantiates an initializer from a configuration dictionary.

#### Example:

    initializer = RandomUniform(-1, 1)
    config = initializer.get_config()
    initializer = RandomUniform.from_config(config)

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| Args ||
|---|---|
| `config` | A Python dictionary. It will typically be the output of `get_config`. |

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| Returns ||
|---|---|
| An Initializer instance. ||

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### `get_config`

[View source](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/init_ops.py#L478-L484)

    get_config()

Returns the configuration of the initializer as a JSON-serializable dict.

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| Returns ||
|---|---|
| A JSON-serializable Python dict. ||

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### `__call__`

[View source](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/init_ops.py#L472-L476)

    __call__(
        shape, dtype=None, partition_info=None
    )

Returns a tensor object initialized as specified by the initializer.

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| Args ||
|---|---|
| `shape` | Shape of the tensor. |
| `dtype` | Optional dtype of the tensor. If not provided use the initializer dtype. |
| `partition_info` | Optional information about the possible partitioning of a tensor. |

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